competencies for he graduates

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Abstract Labor market rewards based on competencies are analyzed using asample of young European higher education (HE) graduates. Estimates of monetaryrewards are obtained from conventional earnings regressions, while estimates totalrewards are based on job satisfaction and derived through ordered probit regres-sions. Results for income show that jobs with higher participative and methodo-logical competency requirements are better paid. The results also show that higher

requirements in terms of competencies increase graduates job satisfaction.

Keywords Assignment theory Competencies Income Job satisfaction Labor market mismatches

Introduction

Human capital competencies, understood as those talents, skills and capabilities ofHE graduates that contribute to multi-factor productivity gains, are perceived as a

key element for sustainable economic growth and development in the globalizeeconomy (Hartog, 1992; Sianesi & Van Reenen, 2003). Increasingly, policy makersare focusing on the importance of competencies with a focus on: linkages betweenproductivity (Buchel, 2002); the demand for competencies and globalization (De laFuente & Ciccone, 2003); the need to take advantage of new technologies (Maria-christina, Santarelli, & Vivarelli, 2003); problems of labor market transition among

A. Garca-Aracil (&)Institute for Innovation and Knowledge Management, INGENIO (CSIC-UPV),

Spanish Council for Scientific Research,Technical University of Valencia,Camino de Vera, 46022, Spaine-mail: [email protected]

R. Van der VeldenROA, University of Maastricht, Maastricht,6200 MD, The Netherlands

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High Educ (2008) 55:219239DOI 10.1007/s10734-006-9050-4

Competencies for young European higher education

graduates: labor market mismatches and their payoffs

Adela Garca-Aracil Rolf Van der Velden

Received: 14 April 2006 / Accepted: 20 December 2006 / Published online: 3 March 2007 Springer Science+Business Media B.V. 2007


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young adults (Bradley & Nguyen, 2004). High levels of education, defined conven-tionally as more years of education, are not enough; modern complex societies aredemanding specific competencies. Individuals can obtain these competenciesthrough experience, training, or more informal means (Hartog, 2001; Rychen &

Salganik, 2003). Formal learning may increase or decrease differences in the abilitiesand levels of competence of individuals (Ishikawa & Ryan, 2002; Neumark &Wascher, 2003; Tyler, Murnane & Willett, 2003).

The introduction of new technologies changes the nature of work, and affects thevalue and content of the competencies required (Mariachristina et al., 2003). Somecompetencies accumulated by workers will become less relevant, while others willbecome crucial. This is standard thinking about technological change and skillsobsolescence and is the logic behind vintage human capital (De Grip, Van Loo &Mayhew, 2002). Evidence of growing wage gaps between more- and less-skilledindividuals has drawn attention to the emergence in economies of a skill-intensity

bias in labor demand (Acemoglu, 1998; Autor, Katz & Krueger, 1998; Berman,Bound & Machin, 1998; Levy & Murnane, 1992). Therefore, technological changegenerates a mismatch between the supply of and demand for competencies, andwage inequality results from the inability of the supply side to keep up with demandrequirements (Witte & Kalleberg, 1995; Thurow, 1975).

These changes have raised concerns about the accuracy of the match between HEand employment of graduates in Europe (Hoogveld, Paas, & Jochems, 2005; Heijke,Meng & Ris, 2003; Teichler & Kehm, 1995; Witte & Kalleberg, 1995). Among theseconcerns, two have attracted the attention of researchers. The first is the identifi-

cation of those competencies that are more relevant to graduates professionalsuccess (Busato, Prins, Elshout & Hamaker, 2000; Robinson, Sparrow, Clegg, &Birdi, 2005; Heijke, Meng & Ramaekers, 2002). The second is whether and howthese competencies are generated (or may be promoted better) by HE systems inEurope (Belfield, Bullock & Fielding, 1999; Dolton & Makepeace, 1990; Kuh, 1999,2001; Leckey & McGuigan, 1997; Pike, 1995; Yang, You & Chen, 2005). Providing aclear answer to these questions is far from straightforward due to the heterogeneityof the productivity-enhancing characteristics of graduates.

Analysis of the matching between job level and level of education based on thenotion of an adequate match as a one-to-one relation is vulnerable to the criticism

that it involves a very rigid view of optimal allocation (Barro & Loewenstein, 1985;Hartog & Oosterbeek, 1988; Jovanovic, 1979, 1984; Topel, 1986). In this sense, joblevel is a variable that measures the complexity of a job, often expressed as therequired ability level of a worker, and sometimes as required education (Hartog,2001). It suggests the existence, for each level of education, of an optimum job leveland the implication that allocation to any other job level is necessarily suboptimal,particularly, with respect to under-utilization. If this match is not optimal, additionallearning through training and work experience will be needed to improve or adjustthe initial competencies acquired during education. Indeed, the importance of

on-the-job training for improving competencies has long been emphasized (Becker,1964; Mincer, 1974) and there have been many debates about its impact on pro-ductivity and wages (Acemoglu & Pischke, 1998; Brown, 1989; Kunze, 2005; Lynch,1992; Pischke, 2000; Raaum & Torp, 2002).

In the absence of data on individual productivities, a major line of research hasdeveloped regarding the effect of education-job mismatches on wages, based onso-called assignment models. Two basic models have been used to study the wage

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effects of over- and under-education. The most common approach is to define thenumber of years of schooling that are adequate or required, for a given job oroccupation (denoted as Er); if E denotes total years of schooling completed, thenyears of over-education are given by Eo = E Er if E > Er and years of under-

education are defined by Eu = Er E if E < Er. The rewards from education arethen separated into rewards in the case of a proper matching and corrections forunder- and over-education (Charlot & Decreuse, 2005; Chevalier, 2003; Groeneveld& Hartog, 2004; Hartog & Oosterbeek, 1988; Verdugo & Verdugo, 1989).

According to those models, individuals working in jobs for which a higher level ofeducation than they actually have, is required (under-education) will often earnmore than individuals with the same level of education working in jobs for whichtheir level of education is appropriate, but less than individuals with the level ofeducation that is actually required (Cohn, 1992; Cohn & Khan, 1995; Duncan &Hoffman, 1981; Hartog & Oosterbeek, 1988). Conversely, individuals working in

jobs for which a lower level of education than they have is required (over-education)will often earn less than individuals with the same level of education working in jobsfor which the level is appropriate (adequate education), but more than individualsworking in an equivalent job with the level of education actually required. That is,the wage effects of over-education are usually stronger than the wage effects ofunder-education.

Hartog (1988) shows that the probability of achieving a higher job level is highestfor individuals whose earnings gain across job level is greatest. The higher the joblevel, the higher the compensation demanded by the individual for further increasing

complexity. Similarly, at higher wage levels, individuals are less reluctant to take onmore demanding jobs. Other authors (Robie, Ryan, Schmieder, Parra, & Smith,1998) suggested a positive relationship between job level and job satisfaction.Higher-level jobs tend to be more complex, provide better working conditions, pay,promotion prospects and supervision and carry greater autonomy and responsibility(Cranny, Smith & Stone, 1992). Additionally, economists have made much progressin understanding that monetary incentives are important, but that there are alsopowerful non-monetary motives that provide incentives for individuals to performspecific tasks (Fehr & Falk, 2002; Igalens & Roussel, 1999). Jobs that are inherentlysatisfying provide an intrinsic reward to those performing them.

A number of economic and other social science studies on the subjective utility ofworking have shown that higher levels of education are unambiguously associatedwith higher levels of satisfaction (Hartog & Oosterbeek, 1988; Ross & VanWillingen, 1997). However, there are several investigations that support the negativeeffects of perceived over-qualification on dimensions of job satisfaction (Hartog,2000; Johnson & Johnson, 2000) and that over-schooling negatively affects jobsatisfaction (Blanchflower & Oswald, 1992; Clark, 1996; Clark & Oswald, 1996;Warr, 1992).

As Hartog (2000) pointed out educational mismatches can be explained by dif-

ferences in the shares of complex jobs and skilled workers. According to assignmenttheory, allocation is optimal when workers are allocated top-down according to theircompetencies, whereby the most competent worker is assigned to the most complexjob and the least competent worker is assigned to the simplest job. Within thisconceptual framework, and taking into account that in our sample all individualshave completed higher education, we tested assignment theory in terms of humancapital competencies in addressing the following:

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To identify which competencies are the most valuable resources for employment(the relationship between competencies and employment is not really clear;however, what is clear is that there is a discrepancy between the acquisition ofcompetencies, e.g. during study, and the requirement for these competencies at a

later time period, e.g. for professional work). To analyze the incidence of different human capital competencies in graduates

payoff, both in terms of income (monetary payoff) and job satisfaction (non-monetary payoff).

To check to what extent the behavior of human capital competencies is similar toformal education in terms of the influence of the mismatch on the individualslabor situation.

The paper is organized as follows: the next section describes the data; the thirdsection presents the problems that arise from the competencies classification used in

this article; the fourth section describes the empirical model; the fifth and sixthsections respectively present the results for income and job satisfaction; and the finalsection provides conclusions and some implications for policy makers.

Acquired and required competencies

The data set used in this paper was taken from a major representative surveycomparing the situations of European HE graduates. More than 36,000 graduates(roughly 3,000 from each country), holding a first HE degree were surveyed four

years after graduation, that is, graduates from 1995 were surveyed in 1999. Thestudy, known as CHEERS (Careers after Higher EducationA European ResearchSurvey), included graduates from 11 European countries: Austria, Czech Republic,Italy, Finland, France, Germany, The Netherlands, Norway, Spain, Sweden and theUnited Kingdom (Schomburg & Teichler, in press; Teichler & Schomburg, in press).For the purposes of our analysis, data from each country were weighted by theproportion of HE students and the population of each country.

The CHEERS survey asked for information on 32 different items relating todemands for and supplies of competencies. Graduates were asked to indicate on anordered scale ranking from 1 (not at all) to 5 (to a very great extent), the strength of

a given competence (the acquired level of competence) at time of graduation and theextent to which this given competence was required in their current work (therequired level of competence). The 32 items are presented in Table 1.

Graduates responses to the question about the acquired level of competenceprovide a self-assessment of the level of competencies built up during HE; graduatesmade retrospective judgments in 1999 about their higher education degrees obtainedin 1995 (four years after their graduation). Responses to the question about the levelof competencies required provide self-reporting measures about their immediate jobsituations. The use of these criteria allows information to be obtained from the

source closest to the actual job situation, and takes account of some specificcircumstances, aspects and features. However, compared to the use of grading by jobanalysts, it lacks uniform instructions and measurements and may produce biasedresults on several counts. Also, respondents may be tempted to portray a desiredsituation (for instance, holding down a job that requires a high level of competence)rather than the true situation, or their answers may be influenced by their needs(physical and psychological), values or work attributes. Finally, graduates

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judgments in assessing their jobs could well be influenced by different workexperience from the graduation (1995) to the time of the survey (1999).

On average, graduates reported lower levels of competence than were required intheir jobs. However, four items received high ratings in terms of acquired compe-tencies: foreign language proficiency; learning abilities; field-specific theoreticalknowledge; and broad general knowledge.

Table 2 presents the differences between acquired and required competencies foreach European country. On average, and as expected, the profiles of acquired andrequired competencies in the Mediterranean countriesItaly, Spain and Franceandthe restAustria, Germany, the Netherlands, United Kingdom, Finland, Sweden,Norway and Czech Republicdiffer. The Mediterranean countries in our sample arecharacterized by lack of competencies mainly relating to field-specific knowledge,economic reasoning, working under pressure, and computer skills, but good compe-tencies in loyalty and integrity, power of concentration and critical thinking.

Table 1 Descriptive statistics for competencies. Europe as a whole (ordered by largest difference)

Items Acquired Required Difference(Acq Req)

Mean Std. Dev. Mean Std. Dev.

Negotiating 2.58 1.05 3.66 1.15 1.08Planning, coordinating and organizing 3.11 1.05 4.11 0.95 1.00Taking responsibilities, decisions 3.38 1.02 4.23 0.88 0.85Time management 3.30 1.04 4.14 0.87 0.84Computer skills 2.97 1.14 3.80 1.12 0.83Working under pressure 3.53 1.08 4.29 0.89 0.76Economic reasoning 2.75 1.14 3.50 1.20 0.75Leadership 2.83 1.06 3.57 1.14 0.74Problem-solving ability 3.62 0.90 4.30 0.79 0.68Oral communication skills 3.62 0.99 4.30 0.83 0.68Assertiveness, decisiveness, persistence 3.50 0.99 4.14 0.84 0.64

Initiative 3.51 0.98 4.11 0.89 0.60Working in a team 3.65 1.04 4.19 0.93 0.54Understanding complex social,

organizational and technical systems2.79 1.02 3.32 1.17 0.53

Documenting ideas and information 3.28 1.05 3.81 1.05 0.53Accuracy, attention to detail 3.70 0.98 4.14 0.86 0.44Reflective thinking, assessing

ones own work3.52 0.94 3.95 0.91 0.43

Working independently 3.95 0.95 4.33 0.86 0.38Adaptability 3.74 0.94 4.11 0.83 0.37Getting personally involved 3.79 0.96 4.07 0.92 0.28Analytical competencies 3.68 0.91 3.95 0.96 0.27

Cross-disciplinary thinking/knowledge 3.39 0.88 3.65 1.01 0.26Field-specific knowledge of methods 3.41 1.00 3.67 1.14 0.26Tolerance, appreciating of different

points of view3.70 0.95 3.96 0.92 0.26

Loyalty, integrity 3.83 1.05 4.06 0.93 0.23Written communication skills 3.85 0.90 4.06 0.96 0.21Critical thinking 3.76 0.94 3.90 0.96 0.14Power of concentration 3.95 0.85 4.05 0.84 0.10Broad general knowledge 3.70 0.82 3.62 1.00 0.08Field-specific theoretical knowledge 3.82 0.93 3.68 1.13 0.14Learning abilities 4.18 0.76 4.03 0.90 0.15Foreign language proficiency 3.06 1.11 2.90 1.38 0.16

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For the non-Mediterranean countries in our sample, Austria and Germany rep-resent one group and the Nordic countriesFinland, Sweden and Norway, togetherthe Netherlands - constitute another. United Kingdom has a more separate positiondefined by the lack of competencies mainly in assertiveness, decisiveness, persis-

tence, working in a team and adaptability. Finally, the Czech Republic is one withmajor deficits in competencies related to planning, coordinating and organizing,problem solving ability, documenting ideas and information, and competencies re-lated to broad general knowledge, field-specific knowledge, and learning abilities.

It should be remembered that these results are descriptive and further work,based on multivariate correspondence analysis (Goodman, 1986; Van der Heijden,De Falguerolles, & De leeuw, 1989), would be needed to check whether the patternof similarities/disparities found in this study is applicable to each individual country.For reasons of space, we present only data regarding Europe as a whole.

Classification of competencies

Discussions on the relevance of some human capital competencies compared toothers often emphasize the importance of particular knowledge, skills and abilities tocarry out an occupation (Hartog, 2001; Rychen & Salganik, 2003). Some labormarket studies relate the skills needed to function in a job and obtain a high salarywith what should be achievable from initial education (Oliva, 2003). Other studieshave found that higher education students who combine a substantial academic

curriculum with various vocational courses do better than students who focus ononly one of these two components (Arum & Shavit, 1995; Bishop, 1995; Kang &Bishop, 1989). In line with these arguments, it is important for policy to identify a setof relevant competencies associated with successful labor market performance.

Competencies are often classified according to the extent to which their appli-cation is related to a particular context, such as a job, a firm, or an occupation. Awell-known classification of competencies is Beckers (1980) distinction betweengeneral and firm-specific competencies, which Nordhaug (1993) refined andextended by distinguishing between competencies specific to firms (firm-specificity),tasks (task-specificity), and economic sectors (industry-specificity).

Heijke et al. (2002) distinguish three groups of competencies: those acquired inschool, which are of direct use in later work; those acquired in school, which facilitateacquisition of new competencies after graduation from school; and those acquiredmainly in a working context. Kellermann (2007) classifies competencies into fivegroups, featuring an academic personality, general-academic (represented bycompetence broad general knowledge), scientific-operative (represented by accuracy,attention to detail), personal-professional (represented by field-specific knowledge ofmethods), social-reflexive (represented by leadership), and physiological-handicraft(represented by manual skills). Bunk (1994) aggregates these competencies into fourdifferent groups: specialized, methodological, participative and socio-individual.Other classifications are added depending on the data available (Allen & Van derVelden, 2001). Thus, there is no general agreement about competency classifications,and economic theory does not provide any clear categorization.

Since competencies are connected with a meaningful connotation, we tried tomake the data more transparent and to overcome the multicollinearity problem inthe list of the 32 competencies available in our sample. To do this, we applied a

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factor analysis to the list of required competencies, bearing in mind that individualswere more likely to refer to their actual job content. Factor analysis providesorthogonal factor scores that are completely uncorrelated. It does not allow us toattribute cause and effect. It does, however, permit us to classify the competencies

into main categories. Principal components analysis (PCA) yielded six factors withan eigenvalue greater than one (8.84, 1.96, 1.81, 1.40, 1.14, 1.02). These six factorsaccounted for 50.6% of the overall variance (i.e., 27.6%, 6.1%, 5.7%, 4.4%, 3.6%,3.2% of the variance, respectively). These percentages represent the proportion oftotal unit variance for each item, which is explained by each factor, after allowing forthe contribution of the other factors. Factor loadings for each item were used tocreate an individual factor score for every respondent, that is, the 32 item scores foreach respondent were reduced to 6 factor scores (see Appendix Table A1). The sixfactors were labeled: organizational (F1), specialized (F2), methodological (F3),generic (F4), participative (F5), socio-emotional competencies (F6).

For the first group, F1 (organizational), we found a Croanbach alpha of 0.72; for F2(specialized) the alpha was 0.75; for F3 (methodological) the alpha was 0.72; for F4(generic) the alpha was 0.72; for F5 (participative) the alpha was 0.77; and for F6 (socio-emotional) the alpha was 0.77. Although there is no generally agreed cut-off, usually avalue of alpha of 0.70 or more is seen as acceptable (Nunnally & Bernstein, 1994).

We defined these factor groups (Table 3) as follow. Organizational competenciesare held by those who are able to work under pressure, to work independently andwith attention to detail. Specialized competencies are held by those who are able tocarry out activities and tasks in their field of work in a responsible and competent

manner and possess the required knowledge and skills to do so. Methodologicalcompetencies are defined as being able to react to problems in a manner that isappropriate, using the procedure expected, and being able to apply experience

Table 3 Categories of competencies

Organizational SpecializedWorking under pressure Field-specific theoretical knowledgeAccuracy, attention to detail Field-specific knowledge of methodsTime management

Working independentlyPower of concentration

Methodological GenericForeign language proficiency Broad general knowledgeComputers skills Cross-disciplinary thinking/knowledgeUnderstanding social,organizational/technical systems

Critical thinking

Documenting ideas and information Oral communications skillsProblem-solving ability Written communications skillsAnalytical competenciesLearning abilities

Participative Socio-emotional competencies

Planning, coordinating and organizing Reflective thinking, assessing ones own workEconomic reasoning Working in a teamNegotiating InitiativeAssertiveness, decisiveness, persistence AdaptabilityLeadership Getting personally involvedTaking responsibilities, decisions Loyalty, integrity

Tolerance, appreciating of different point of view

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gained to find sensible solutions to other problems. Generic competencies can bedefined as those competencies that can be applied across a broad range of contexts.This indicates that generic competencies imply more than just general knowledge inthe strict sense; it also includes critical thinking and oral and written communications

skills. Participative competencies are held by those who are able to contribute to-wards constructing the working environment in their workplace and beyond, whocan plan ahead, assume tasks, take decisions and are willing to assume responsibility.Finally, individuals who are able to work cooperatively with others and who showteam-oriented behavior and interpersonal understanding are described as havingsocio-emotional competencies.

Empirical model

In addition to identification of the most important acquired and required compe-tencies, we are particularly interested in the returns on human capital competenciesin the labor market, in terms of both income and job satisfaction. To obtain thereturns for income, we applied job-matching theory, which expects that moredemanding jobs will be result in higher incomes, income premiums for surpluses, andincome penalties for deficits in competencies. For job satisfaction, we performed thesame analysis. Here we expected different results: working in a job that requires ahigh level of competencies has a positive effect on job occupants satisfaction, butsurpluses in competencies are an important cause of job dissatisfaction, while the

effects of deficits are ambiguous depending on the individual challenge. As men-tioned above, we applied factor analysis to the required competencies. This yieldedsix factors. To define deficits and surpluses, we used the same factor loadings foracquired competencies and calculated the difference. As both acquired and requiredcompetencies were standardized before applying factor analysis, the resultingdifferences refer to relative differences.

To analyze the effects of these six competence-categories requirements, surpluses,and deficits related to graduates income and job satisfaction, we estimated a con-ventional earnings regression for income using OLS estimation, and an orderedprobit regression for job satisfaction to reflect the ordinal character of the answers

on job satisfaction scores. In our survey, higher education graduates were asked:Altogether, to what extent are you satisfied with your current job? Respondents couldchoose from five rankings from 1 (very dissatisfied) to 5 (very satisfied). Self-assessments of job satisfaction indicate how people value the whole package of bothmonetary and non-monetary returns from their jobs, according to their personalpreferences. Survey responses for job satisfaction have been used in economicanalysis as proxy data for utility from work, with job satisfaction, in its turn, being akey determinant of total well-being for working individuals (Van Praag, 1991).

To facilitate a comparison of these effects, two specifications were estimated.First, we assessed a model containing indicators of the required level of compe-tencies, with control variables for personal characteristics, job characteristics,occupational titles, fields of study, job in own domain, dummies for each country andfor the distinction between university institutions and other HE institutions (ModelI). Then, in order to ascertain to what extent surpluses and/or deficits in compe-tencies have effects on income and job satisfaction, we added indicators ofmismatches according to the competencies required for the job (Model II).

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We used working hours and size of firms as job attributes. In public sectoremployment, full-time jobs and permanent contracts have specific characteristicsthat many people consider desirable, thus we also included a dummy variable foreach. The six dummies representing the occupational titles were: legislators, senior

officials and managers; professionals; technicians and associate professionals; clerks;service workers and, shop and market workers; skilled agricultural and fisheryworkers, and elementary occupations.

In addition to the effects of a mismatch between acquired and required level ofcompetencies, we took into account the effects of graduating in a specific field ofstudy. We used dummies for eight different fields of study: Education, Humanities,Social Sciences, Law, Natural Sciences, Mathematics, Medical Sciences and Engi-neering. We also defined a dummy for those working in their own field-specificeducational domain. Job in own domain is measured as holding a position for whichthe own field of study is by far the best, or for which a related field of study could

provide the same sort of grounding. Personal characteristics such as age and genderwere included as control variables.

We made a distinction between university institutions and other HE institutionsto test for possible differences between the effects of both types of institutions on thecareers of graduates. To provide a more detailed analysis, we used dummies for eachEuropean country included in our sample: Austria, Czech Republic, Italy, Finland,France, Germany, The Netherlands, Norway, Spain, Sweden and the UnitedKingdom. Descriptive statistics for all these variables are reported in the Appendix(see Table A2).

Effects of competencies on income

Table 4 shows the results for a conventional earnings regression (natural logarithmof income). Model I shows that 39% of the income differences can be explained bythe variables in the model. Although this percentage seems low, the relativehomogeneity of the group in terms of basic human capital aspects should be bornein mind. There were in fact differences among the competence-categories consid-ered. We observed that participative and methodological competencies seemed to

be much more important than other competencies for explaining income differ-ences. One standard deviation increase in the required level of participative com-petencies yielded an income increase of some 6%, and a similar increase in therequired level of methodological competencies yielded an income increase of some4%. Socio-emotional and generic competencies had a similar, but smaller effect onincome increase. With respect to specialized competencies, income analysis showsthat the required level did not have a significant effect. This result must be inter-preted with care bearing in mind that in our analysis we used occupational titles ascontrol variables. A separate analysis (not shown here) which did not consider

occupational titles showed a significant positive effect of specialized competencieson income. Therefore, the analysis presented in Table 4 indicates that the effect ofspecialized competencies on job performance is mediated by type of job. Finally,organizational competencies had a negative effect. This might indicate that thesecompetencies are not rewarded in the first years of professional careers.

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Table 4 OLS parameter estimates for annual gross income. European countries

Model I Model II

Coeff. t-values Coeff. t-values

Competencies requiredOrganizational 0.012* 4.056 0.013* 3.335Specialized 0.001 0.380 0.008*** 1.846Methodological 0.040* 12.752 0.056* 13.702Generic 0.018* 5.813 0.003 0.746Participative 0.052* 16.661 0.046* 11.329Socio-emotional 0.023* 7.524 0.016* 4.108Surplus of competenciesOrganizational 0.003 0.598Specialized 0.009*** 1.745Methodological 0.013** 2.247

Generic 0.020* 4.020Participative 0.006 1.060Socio-emotional 0.017* 3.296Deficit of competenciesOrganizational 0.002 0.419Specialized 0.005 1.101Methodological 0.036* 6.098Generic 0.014* 2.552Participative 0.007 1.588Socio-emotional 0.003 0.562Personal characteristicsFemale 0.069* 11.463 0.069* 11.347

Age 0.011* 7.815 0.012* 8.236Job characteristicsHours worked per week 0.259* 18.999 0.259* 18.974Private sector 0.081* 12.212 0.079* 11.964Small firm 0.144* 20.615 0.144* 20.607Full-time job 0.263* 22.569 0.261* 22.469Permanent contract 0.126* 17.166 0.125* 17.075Occupational titlesLegislators, senior official

and managers(ref. Elementary occupations)

0.188* 16.207 0.183* 15.780

Professionals 0.132* 15.324 0.130* 15.002

Technicians and associateprofessionals 0.080* 7.546 0.080* 7.486

Clerks 0.018 1.181 0.020 1.310Service workers 0.020 0.860 0.023 0.991Field of studiesEducation (ref. Engineering) 0.081* 5.889 0.067* 4.810Humanities 0.117* 11.194 0.105* 9.830Social Sciences 0.030* 3.790 0.026* 3.227Law 0.098* 8.069 0.085* 6.906Natural Sciences 0.079* 7.115 0.074* 6.648Mathematics 0.095* 7.330 0.085* 6.504Medical Sciences 0.045* 3.664 0.056* 4.512

Universities vs. H.E. Institutions 0.038* 5.531 0.038* 5.479Job in own domain 0.058* 8.705 0.054* 8.082Intercept 1.648* 25.848 1.646* 25.602Observations 24,414 24,414Adjusted R-squared 0.39 0.40

*p 0.01; **p 0.05; ***p 0.10 (effects of country dummies not shown)

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In Model II, indicators of competencies mismatches were added to the earningequation. This slightly improves the model fit, resulting in an adjusted R-squared of0.40. We observed that the weight of some competencies increased, e.g. methodo-logical competencies, and others decreased, e.g. participative, generic and socio-

emotional competencies.In terms of the effect of the mismatches, there was a significant positive effect of

surpluses in methodological competencies, which confirms the prediction thatmethodological competence pay off even when they were not required. The pre-dicted negative effect of deficits in this competence was also observed. However, thepredictions of assignment theory and the results obtained in earlier research, that theeffects of surpluses in competencies are considerably greater than those for deficits,were not confirmed by our results. Each additional standard deviation surplus inmethodological competencies yielded an income increase of some 1%. Each addi-tional standard deviation deficit in methodological competencies led to a decrease in

income of 3%.Other results were the reverse of what we might expect on the basis of assignment

theorywages premiums for surplus, and wage penalties for deficits in competen-cies. Having a higher level of generic, socio-emotional and specialized competenciesthan the job required had a negative effect on income. This is likely to be the resultof the presence of strong deficits in other competencies not considered in ouranalysis, e.g. extra-curricula competencies, especially if these deficits in unmeasuredcompetencies are strongly correlated with surpluses in measured competencies. Inthe case of specialized competencies in particular, this might be a valid explanation

of the negative effect of a surplus. If someone works in a job outside his/her field ofstudy, then he/she will experience a surplus of specialized competencies and a deficitof the competencies needed in the actual area of work. If these other competenciesare not measured, then the surplus of specialized competencies will show a negativesign. On the other hand, surpluses and deficits in participative and organizationalcompetencies appeared to have no effect on income.

The results for the rest of the key variables considered in both Model I andModel II were similar. Consistent with other work in this area, we found thatfemale graduates earned less than their male counterparts, and that age (capturingwork experience) had a positive effect. On the other hand, those working in the

private sector, or on permanent contracts, earned more than those working in thepublic sector or on temporary contracts. Positive effects were also found for full-time jobs and number of hours worked, and negative effects for those working insmall firms.

With respect to occupational titles, both models provide evidence suggesting thatindividuals working in more demanding jobs achieve higher incomes. Legislators,senior officials, managers, professionals, technicians and associate professionalsearned more than their counterparts in less demanding occupations. When we ex-plore the segmentation of different educational fields, we note that graduates in

Education, Humanities, Social Science, Law and Natural Sciences earned less thanthe reference category (Engineering). However, Mathematics (data processing andcomputer specialists included) and Medical Sciences graduates earned more. Itmight be expected that there is a high likelihood that graduates from Mathematics,Medical Sciences and Engineering will work within their own educational domainsand that therefore they will benefit from an income premium (due to their goodcompetence match). The results in Table 4 show that working within ones particular

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knowledge domain increases income by 5%. Finally, having received a universityeducation rather than being educated at another type of HE institution, yields anincrease in income of around 4%.

Effects of competencies on job satisfaction

The effects of competency mismatches on job satisfaction are shown in Table 5. Toreflect the ordinal character of the responses about job satisfaction, we used anordered probit model. Maximum-likelihood estimation of the models was carriedout using the Newton-Raphson algorithm based on second derivates (Green, 1997).To facilitate a comparison of income effects, the same set of independent variableswas included. Annual gross income was also included as an additional controlvariable.

Table 5 Ordered probit estimates for job satisfaction. European countries

Model I Model II

Coeff. Sig. Coeff. Sig.

Competencies requiredOrganizational 0.103* 13.126 0.086* 8.887Specialized 0.129* 15.876 0.114* 10.350

Methodological 0.069* 8.527 0.077* 7.415Generic 0.194* 24.831 0.132* 12.847Participative 0.094* 11.830 0.103* 9.943Socio-emotional 0.180* 22.868 0.151* 15.445

Surplus of competenciesOrganizational 0.071* 5.372Specialized 0.003 0.245Methodological 0.022 1.520Generic 0.102* 8.167Participative 0.017 1.272Socio-emotional 0.052* 3.925

Deficit of competenciesOrganizational 0.014 1.099Specialized 0.035* 2.974Methodological 0.001 0.006Generic 0.038* 2.737Participative 0.010 0.910Socio-emotional 0.022*** 1.871

Personal characteristicsFemale 0.008 0.536 0.010 0.636Age 0.037* 10.137 0.037* 9.965

Job characteristicsAnnual gross income 0.325* 19.867 0.319* 19.442Hours worked per week 0.031 0.894 0.035 0.996Private sector 0.144* 8.464 0.143* 8.406Small firm 0.106* 5.904 0.103* 5.689Full-time job 0.026 0.873 0.024 0.800Permanent contract 0.115* 6.135 0.111* 5.905

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Model I shows that job satisfaction was strongly influenced by the required levelof competencies. We observe that a high requirement in terms of generic, socio-emotional, specialized, organizational and participative competencies had a positiveeffect on job satisfaction.

Again, Model II includes indicators for mismatches in competencies. And again,an accurate match between competencies acquired and competencies required in the

job, increased job satisfaction significantly. As expected, graduates who reported asurplus of competencies had much less job satisfaction than those with the rightcompetencies for the job. The exception was a surplus in specialized, methodologicaland participative competencies. On the other hand, deficits in generic, specializedand socio-emotional competencies increased satisfaction, probably due to the factthat these deficits were viewed as a personal challenge.

The results for the remaining control variables were similar for both models. Aspredicted by the conventional literature, age had a negative effect (Clark & Oswald,1996). Also, as might be expected, income had a fairly strong effect on job satis-faction, and graduates working in small firms on permanent contracts also reportedreasonable job satisfaction. Public sector workers reported higher levels of jobsatisfaction than private sector ones.

With respect to occupational titles, both models provide evidence that individualsworking in more complex jobs received more satisfaction. Legislators, seniorofficials, managers, professionals, technicians and associate professionals were moresatisfied in their work than their counterparts in less senior occupations. It could be

Table 5 continued

Model I Model II

Coeff. Sig. Coeff. Sig.

Occupational titlesLegislators, senior official

and managers(ref. Elementary occupations)

0.153* 5.153 0.150* 5.041

Professionals 0.172* 7.769 0.172* 7.771Technicians and

associate professionals0.106* 3.911 0.109* 4.025

Clerks 0.114* 3.007 0.116* 3.071Service workers 0.043 0.729 0.043 0.721

Field of studiesEducation (ref. Engineering) 0.026 0.727 0.005 0.154

Humanities 0.081* 3.011 0.032 1.178Social Sciences 0.067* 3.244 0.062* 2.965Law 0.137* 4.402 0.118* 3.726Natural Sciences 0.036 1.269 0.045 1.600Mathematics 0.143* 4.267 0.129* 3.838Medical Sciences 0.089* 2.850 0.077* 2.452Universities vs. H.E. Institutions 0.107* 6.054 0.117* 6.600Job in own domain 0.223* 13.071 0.214* 12.459Observations 24,414 24,414LR v2(38); LR v2(50) 4,259.49 4,411.07Log likelihood 30,991.35 30,910.73

*p 0.01; **p 0.05; ***p 0.10 (effects of country dummies not shown)

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said that high-level jobs tend to be more complex and have better workingconditions, pay, promotion prospects, supervision, autonomy and responsibility, andall these characteristics are associated with job satisfaction.

On the other hand, graduates in Humanities, Medical Sciences, Social Sciences

and Law reported less job satisfaction with respect to the reference category(Engineering). Mathematics graduates were the most satisfied with their jobs.Finally, a university education rather than another type of HE, and working insideones own domain of expertise increased the level of job satisfaction.

Conclusions

In this paper we analyzed the relationship between the payoffs from the required,surplus, and deficit human capital competencies in terms of both income (monetary

payoff) and job satisfaction (non-monetary payoff) of graduates. In assignmenttheory the concepts of educational and competencies mismatches are assumed to beclosely related: educational mismatches imply competency mismatches, which inturn have an effect on income. Due to the fact that all individuals, in our sample hadcompleted HE, we analyzed the incidence of different human capital competenciesin graduates payoffs. Surpluses and deficits in competencies were measured byasking graduates to evaluate the job they held in terms of the level of competenciesthey thought was required to perform them adequately compared to their actualacquired level.

Six different categories of competencies were explored, namely organizational,specialized, methodological, generic, participative and socio-emotional competen-cies to give a more detailed analysis of the different roles and payoffs of the com-petencies in the labor market. Other variables, such as personal characteristics, jobcharacteristics, occupational titles, field of study, job in own domain and the dis-tinction of graduates from university institutions versus those from other HE insti-tutions, were also considered. Control variables for the 11 European countries in oursample were also taken into account.

The results provide strong support for the assumption that the match betweenindividual human capital competencies and the characteristics of the job does

matter. Our findings from the income analysis, suggest that those jobs with a highrequirement for participative and methodological competencies were the best paidand that jobs with a high requirement for organizational competencies were theworst paid. Specialized competencies had an indirect effect in their allocation toprofessional jobs. In short, we observe that monetary rewards depend most oncompetencies related to the capacity of the individual to manage a complex situationwith leadership and personal involvement. Attitudes towards work (rather thanknowledge) were the characteristics that received the highest financial recognition inthe labor market for young graduates. Our results for job satisfaction support the

statement that working in a job that requires a high level of competencies has apositive effect on the job-holders satisfaction.The analysis of competency mismatches shows that a surplus of methodological

competencies has a positive effect on income, and a deficit has a negative effect onincome. This was the only case that behaved as predicted by assignmenttheorywage premiums for surpluses and wage penalties for deficits in competen-cies. The behavior in terms of the remaining competencies was different and

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non-systematic. Of particular interest was the case of generic competencies: asurplus was penalized and a deficit awarded. One explanation for this could be thatassignment theory does not hold for competencies (all or part of them). Anotherpossibility is that, because we were analyzing jobs occupied by recent graduates,

salaries were more related to the job than to the individuals actual performance. Interms of job satisfaction, we found that competencies surplus was an important causeof job dissatisfaction, the exception being methodological, specialized and partici-pative competencies. Deficits in generic, specialized and socio-emotional compe-tencies apparently increase satisfaction. This is likely due to the types of jobs wherethe requirements for these competencies is high (scientists, medicine, and so on), andto the personal challenge implied.

Consistent with earlier work in this area, we found that female graduates earnedless, but were as satisfied in their jobs as their male counterparts. In addition, youngEuropean graduates with permanent and full-time jobs in the private sector or in

large firms earned more, although their preference was for public sector jobs andwork in small firms. All round, a good salary was the main factor involved inincreased job satisfaction. High-level jobs were related to both high-income and highlevels of satisfaction. Fields such as Mathematics and Engineering generated highincomes and job satisfaction. Working inside ones particular domain of expertiseand having a university education rather than being educated at some other type ofHE institution increased both income and job satisfaction.

We can conclude from our results that European HE systems need to have moreawareness with the realities of the labor market. Further research on competencies

will increase understanding about how the graduate labor market works. Both thetitles and content of occupations are changing. Traditionally, at least in mostEuropean countries, theoretical and specific knowledge have been the key to highprofessional positions, related to a HE diploma. A new and more dynamic labormarket, and the massive presence of HE graduates in the labor market, has created anew situation in which these competencies are not so much in demand (takingmonetary rewards as a proxy for demand) in the labor market. The new situationrequires individuals with participative, methodological and socio-emotional com-petencies. Enhancing these competencies in the educational process requires anapproach that is different from what has traditionally been offered by HE institu-

tions, an approach that is focused on active learning, stimulation of relationships andcooperation of individuals, promoting multidisciplinary approaches, and so on. Insummary, current social demand requires a different style learning process that is farremoved from the traditional methods based on passive accumulation of knowledge.In addition, it should be kept in mind that the diversity pattern found in the profilesof the acquired and required level of competencies among the European countriesanalyzed in our sample demonstrates that these changes to the learning process willneed policies tailored to individual country situations.

Thus, our results open a number of interesting areas for discussion: What is the

relative importance of specific as opposed to more generic competencies? Are dif-ferent competencies required during the transition from education to work than inlater career stages? What are the competencies that graduates need for quickproductivity returns, and which ones are more important for longer-term employ-ability? What are the implications for the curriculum? These questions are of great

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importance, not only from a scientific point of view, but also to enable a moreeffective and efficient organization of education.

Appendix

Table A2 Descriptive statistics

Variable Mean Std. Dev. Min. Max.

Organizational 0.01 0.93 6.01 3.43Specialized 0.01 0.91 3.72 2.54Methodological 0.01 0.93 4.82 3.21Generic 0.01 0.91 4.99 4.04Participative 0.02 0.92 4.59 4.43Socio-emotional 0.03 0.93 6.04 3.42

Table A1 Rotated factor matrix for required competencies

Items F1 F2 F3 F4 F5 F6

Working under pressure 0.49 0.03 0.18 0.07 0.43 0.11Accuracy, attention to detail 0.71 0.14 0.13 0.01 0.06 0.07Time management 0.52 0.02 0.07 0.07 0.42 0.10Working independently 0.48 0.11 0.06 0.25 0.23 0.02Power of concentration 0.66 0.17 0.14 0.15 0.05 0.22Field-specific theoretical knowledge 0.10 0.85 0.01 0.10 0.01 0.02

Field-specific knowledge of methods 0.07 0.86 0.07 0.06 0.05 0.06Foreign language proficiency 0.03 0.05 0.54 0.12 0.02 0.04Computer skills 0.11 0.06 0.71 0.05 0.08 0.02Understanding social, organizational/technical

systems0.07 0.07 0.52 0.23 0.37 0.04

Documenting ideas and information 0.19 0.17 0.50 0.23 0.21 0.18Problem-solving ability 0.30 0.30 0.41 0.08 0.31 0.21Analytical competencies 0.26 0.37 0.53 0.10 0.09 0.18Learning abilities 0.36 0.24 0.42 0.18 0.03 0.31Broad general knowledge 0.04 0.08 0.06 0.72 0.17 0.07Cross-disciplinary thinking/knowledge 0.03 0.19 0.21 0.67 0.20 0.05Critical thinking 0.32 0.22 0.13 0.39 0.08 0.38

Oral communication skills 0.24 0.02 0.01 0.50 0.27 0.31Written communication skills 0.34 0.07 0.26 0.54 0.06 0.13Planning, coordinating and organizing 0.11 0.06 0.31 0.23 0.58 0.14Economic reasoning 0.09 0.06 0.36 0.04 0.59 0.07Negotiating 0.14 0.08 0.07 0.15 0.67 0.12Assertiveness, decisiveness, persistence 0.41 0.10 0.03 0.19 0.43 0.31Leadership 0.03 0.10 0.03 0.17 0.65 0.33Taking responsibilities, decisions 0.19 0.17 0.07 0.19 0.61 0.32Reflective thinking, assessing ones own work 0.30 0.27 0.14 0.30 0.13 0.40Working in a team 0.01 0.06 0.22 0.01 0.21 0.65Initiative 0.25 0.09 0.13 0.21 0.41 0.44Adaptability 0.19 0.01 0.08 0.02 0.19 0.67Getting personally involved 0.35 0.10 0.07 0.23 0.24 0.37Loyalty, integrity 0.28 0.04 0.09 0.17 0.13 0.44Tolerance, appreciating of different

points of view0.09 0.08 0.03 0.34 0.15 0.61

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Table A2 continued

Variable Mean Std. Dev. Min. Max.

Surplusorganizational 0.42 0.65 0 6.25

Surplusspecialized 0.44 0.72 0 6.25Surplusmethodological 0.39 0.50 0 6.00Surplusgeneric 0.42 0.71 0 7.28Surplusparticipative 0.41 0.64 0 5.67Surplussocio-emotional 0.40 0.65 0 6.98Deficitorganizational 0.36 0.61 0 6.44Deficitspecialized 0.42 0.67 0 4.95Deficitmethodological 0.33 0.54 0 5.11Deficitgeneric 0.37 0.59 0 5.17Deficitparticipative 0.48 0.76 0 5.87Deficitsocio-emotional 0.39 0.66 0 6.27Female 0.50 0.50 0 1

Age 29.14 2.42 26 35Hours worked per week 37.20 7.33 10 60Private sector 0.70 0.46 0 1Size firm: small 0.22 0.41 0 1Full-time job 0.89 0.31 0 1Permanent contract 0.78 0.42 0 1Legislators, senior official

and managers0.09 0.28 0 1

Professionals 0.54 0.50 0 1Technicians and associate

professionals0.15 0.36 0 1

Clerks 0.03 0.18 0 1

Service workers 0.01 0.10 0 1Elementary workers 0.18 0.11 0 1Education 0.05 0.23 0 1Humanities 0.12 0.33 0 1Social Sciences 0.31 0.46 0 1Law 0.07 0.26 0 1Natural Sciences 0.09 0.29 0 1Mathematics 0.06 0.23 0 1Medical Sciences 0.08 0.27 0 1Engineering 0.22 0.41 0 1Universities 0.76 0.42 0 1Job in own domain 0.74 0.44 0 1

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